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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Perspective: Size selected clusters for catalysis and electrochemistry

We report that size-selected clusters containing a handful of atoms may possess noble catalytic properties different from nano-sized or bulk catalysts. Size- and composition-selected clusters can also serve as models of the catalytic active site, where an addition or removal of a single atom can have a dramatic effect on their activity and selectivity. In this Perspective, we provide an overview of studies performed under both ultra-high vacuum and realistic reaction conditions aimed at the interrogation, characterization and understanding of the performance of supported size-selected clusters in heterogeneous and electrochemical reactions, which address the effects of cluster size, cluster composition, cluster-support interactions and reaction conditions, the key parameters for the understanding and control of catalyst functionality. Computational modelling based on density functional theory sampling of local minima and energy barriers or ab initio Molecular Dynamics simulations is an integral part of this research by providing fundamental understanding of the catalytic processes at the atomic level, as well as by predicting new materials compositions which can be validated in experiments. Lastly, we discuss approaches which aim at the scale up of the production of well-defined clusters for use in real world applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Three rate-determining protein roles in photosynthetic O 2 -evolution addressed by time-resolved experiments on genetically modified photosystems

Light-driven water splitting by plants, algae and cyanobacteria is pivotal for global bioenergetics and biomass formation. A manganese cluster bound to the photosystem II proteins catalyzes the complex reaction at high rate, but the rate-determining factors are insufficiently understood. Here we trace the oxygen-evolution transition by time-resolved polarography and infrared spectroscopy for cyanobacterial photosystems genetically modified at two strategic sites, complemented by computational chemistry. Our results highlight three rate-determining roles of the protein environment of the metal cluster: acceleration of proton-coupled electron transfer, acceleration of substrate-water insertion after O 2 -formation, and balancing of rate-determining enthalpic and entropic contributions. Whereas in general the substrate-water insertion step may be unresolvable in time-resolved experiments, here it likely becomes traceable because of deceleration by genetic modification. Our results may stimulate new time-resolved experiments on substrate-water insertion in photosynthesis, clarification of enthalpy-entropy compensation in enzyme catalysis, and knowledge-guided development of inorganic catalyst materials.

Bioenergetics↗
DOE OSTI2017

Building Halo Merger Trees from the Q Continuum Simulation

Cosmological N-body simulations rank among the most computationally intensive efforts today. A key challenge is the analysis of structure, substructure, and the merger history for many billions of compact particle clusters, called halos. Effectively representing the merging history of halos is essential for many galaxy formation models used to generate synthetic sky catalogs, an important application of modern cosmological simulations. Generating realistic mock catalogs requires computing the halo formation history from simulations with large volumes and billions of halos over many time steps, taking hundreds of terabytes of analysis data. We present fast parallel algorithms for producing halo merger trees and tracking halo substructure from a single-level, density-based clustering algorithm. Merger trees are created from analyzing the halo-particle membership function in adjacent snapshots, and substructure is identified by tracking the "cores" of merging halos - sets of particles near the halo center. Core tracking is performed after creating merger trees and uses the relationships found during tree construction to associate substructures with hosts. The algorithms are implemented with MPI and evaluated on a Cray XK7 supercomputer using up to 16,384 processes on data from HACC, a modern cosmological simulation framework. We present results for creating merger trees from 101 analysis snapshots taken from the Q Continuum, a large volume, high mass resolution, cosmological simulation evolving half a trillion particles.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Coupled cluster calculations on TiO2 nanoclusters

The excitation energies of the four lowest-lying singlet excited states of the TiO2 Ti2O4 and Ti3O6 clusters are calculated by a variety of different Equation-of-Motion Coupled Cluster (EOM-CC) approaches in order to obtain benchmark values for the optical excitations of titanium dioxide clusters. More specifically we investigate what is the effect of the inclusion of triple excitations "triples" in the (EOM-)CC scheme on the calculated excited states of those clusters. While for the monomer and dimer the inclusion of triples causes only a rigid shift in the excitation energies, in the case of the trimer the crossing of the interested states is observed. Coupled cluster approaches where triples are treated perturbatively were found to offer no advantage over EOM-CCSD, whereas the active-space methods (EOM-CCSDt(II/I)) proved to yield results very close to the full EOM-CCSDT, but at a much lower computational cost.

calculations↗
DOE OSTI2014

Relativistic coupled cluster study of diatomic compounds of Hg, Cn, and Fl

The structure and energetics of eight diatomic heavy-atom molecules are presented. These include the species MAu, M{sub 2}, and MHg, with M standing for the Hg, Cn (element 112), and Fl (element 114) atoms. The infinite-order relativistic 2-component Hamiltonian, known to closely reproduce 4-component results at lower computational cost, is used as framework. High-accuracy treatment of correlation is achieved by using the coupled cluster scheme with single, double, and perturbative triple excitations in large converged basis sets. The calculated interatomic separation and bond energy of Hg{sub 2}, the only compound with known experimental data, are in good agreement with measurements. The binding of Fl to Au is stronger than that of Cn, predicting stronger adsorption on gold surfaces. The bond in the M{sub 2} species is strongest for Fl{sub 2}, being of chemical nature; weaker bonds appear in Cn{sub 2} and Hg{sub 2}, which are bound by van der Waals interactions, with the former bound more strongly due to the smaller van der Waals radius. The same set of calculations was also performed using the relativistic density functional theory approach, in order to test the performance of the latter for these weakly bound systems with respect to the more accurate coupled cluster calculations. It was found that for the MAu species the B3LYP functional provides better agreement with the coupled cluster results than the B88/P86 functional. However, for the M{sub 2} and the MHg molecules, B3LYP tends to underestimate the binding energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Evaluating HPC Scheduling Strategies for Urgent Workloads

Scientific computing centers increasingly face workloads with diverse urgency requirements, driven by applications that demand rapid or even immediate execution. Appropriately configured scheduling policies can significantly improve both user satisfaction and overall cluster utilization. In this work, we present a systematic analysis of scheduler configurations under scenarios where a fraction of jobs have urgent computing needs. We evaluate multiple job scheduling simulators, develop a lightweight job-submission emulation framework, and create tools to analyze and visualize the resulting scheduling data. Our study identifies key trade-offs between responsiveness, fairness, and efficiency, and offers a set of practical scheduling configurations (particularly for Slurm) that can be tailored to HPC environments supporting mixed-urgency workloads.

Maheshwari, Ketan [ORNL] (ORCID:000000033800662X)↗
DOE OSTI2023

Thermofield Theory for Finite-Temperature Electronic Structure

Wave function methods have offered a robust, systematically improvable means to study ground-state properties in quantum many-body systems. Theories like coupled cluster and their derivatives provide highly accurate approximations to the energy landscape at a reasonable computational cost. Analogues of such methods to study thermal properties, though highly desirable, have been lacking because evaluating thermal properties involve a trace over the entire Hilbert space, which is a formidable task. Besides, excited-state theories are generally not as well studied as ground-state ones. In this mini-review, we present an overview of a finite-temperature wave function formalism based on thermofield dynamics to overcome these difficulties. Thermofield dynamics allows us to map the equilibrium thermal density matrix to a pure state, i.e., a single wave function, albeit in an expanded Hilbert space. Ensemble averages become expectation values over this so-called thermal state. Around this thermal state, we have developed a procedure to generalize ground-state wave function theories to finite temperatures. As explicit examples, we highlight formulations of mean-field, configuration interaction, and coupled cluster theories for thermal properties of Fermions in the grand-canonical ensemble. To assess the quality of these approximations, we also show benchmark studies for the one-dimensional Hubbard model, while comparing against exact results. We will see that the thermal methods perform similarly to their ground-state counterparts, while merely adding a prefactor to the asymptotic computational cost. Furthermore, they also inherit all the properties, good or bad, from the ground-state methods, signifying the robustness of our formalism and the scope for future development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Quantum circuit cutting with maximum-likelihood tomography

Abstract We introduce maximum-likelihood fragment tomography (MLFT) as an improved circuit cutting technique for running clustered quantum circuits on quantum devices with a limited number of qubits. In addition to minimizing the classical computing overhead of circuit cutting methods, MLFT finds the most likely probability distribution for the output of a quantum circuit, given the measurement data obtained from the circuit’s fragments. We demonstrate the benefits of MLFT for accurately estimating the output of a fragmented quantum circuit with numerical experiments on random unitary circuits. Finally, we show that circuit cutting can estimate the output of a clustered circuit with higher fidelity than full circuit execution, thereby motivating the use of circuit cutting as a standard tool for running clustered circuits on quantum hardware.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Correlating and Simulating Socio-Demographically Driven Residential End-Use Activity Schedules

Incorporating socio-demographic and behavioral considerations into decision-support tools is crucial for identifying gaps and addressing consumer needs to ensure reliable and affordable energy solutions. In energy simulation models, the correlation between socio-demographics and time-use behavior is not well-captured. Thus, we developed a large-scale simulation workflow to generate schedules for 10 residential activities across 24 population segments defined by age, income, and employment status. Using pre-pandemic 2015-2019 American Time Use Survey (ATUS) data, we used ANOVA to confirm the correlation between demographic factors and time use. We explored three k-modes clustering methods-backward, forward, and a new hybrid approach-to delineate the occupancy patterns based on demographics. Using the probability of cluster membership for each population segment and a time inhomogeneous Markov chain to generate activity transition probabilities for each cluster, we simulated 50,000 schedules per segment and validated them against the ATUS data. The hybrid method produced the most socio-demographically differentiated clusters while demonstrating comparable performance to other approaches, with an overall root mean square error of 0.12 for both weekday and weekend schedules. Thus, the hybrid method, where each cluster is dominated by certain demographic segments and occupancy patterns, offers more modeling versatility in terms of scenario analysis. The new workflow improves the socio demographic differentiation of energy consumption by considering differences in time use. This approach enables future research on demographically segmented time of use (TOU) energy consumption, including impacts of TOU utility bills and rate analysis, long-run marginal emissions, and energy retrofits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Transition properties from the Hermitian formulation of the coupled cluster polarization propagator

Theory of one-electron transition density matrices has been formulated within the time-independent coupled cluster method for the polarization propagator [R. Moszynski, P. S. Żuchowski, and B. Jeziorski, Coll. Czech. Chem. Commun. 70, 1109 (2005)]. Working expressions have been obtained and implemented with the coupled cluster method limited to single, double, and linear triple excitations (CC3). Selected dipole and quadrupole transition probabilities of the alkali earth atoms, computed with the new transition density matrices are compared to the experimental data. Good agreement between theory and experiment is found. The results obtained with the new approach are of the same quality as the results obtained with the linear response coupled cluster theory. The one-electron density matrices for the ground state in the CC3 approximation have also been implemented. The dipole moments for a few representative diatomic molecules have been computed with several variants of the new approach, and the results are discussed to choose the approximation with the best balance between the accuracy and computational efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Accurate ab initio potential energy surface, thermochemistry, and dynamics of the F{sup −} + CH{sub 3}F S{sub N}2 and proton-abstraction reactions

We develop a full-dimensional global analytical potential energy surface (PES) for the F{sup −} + CH{sub 3}F reaction by fitting about 50 000 energy points obtained by an explicitly correlated composite method based on the second-order Møller–Plesset perturbation-F12 and coupled-cluster singles, doubles, and perturbative triples-F12a methods and the cc-pVnZ-F12 [n = D, T] basis sets. The PES accurately describes the (a) back-side attack Walden inversion mechanism involving the pre- and post-reaction (b) ion-dipole and (c) hydrogen-bonded complexes, the configuration-retaining (d) front-side attack and (e) double-inversion substitution pathways, as well as (f) the proton-abstraction channel. The benchmark quality relative energies of all the important stationary points are computed using the focal-point analysis (FPA) approach considering electron correlation up to coupled-cluster singles, doubles, triples, and perturbative quadruples method, extrapolation to the complete basis set limit, core-valence correlation, and scalar relativistic effects. The FPA classical(adiabatic) barrier heights of (a), (d), and (e) are −0.45(−0.61), 46.07(45.16), and 29.18(26.07) kcal mol{sup −1}, respectively, the dissociation energies of (b) and (c) are 13.81(13.56) and 13.73(13.52) kcal mol{sup −1}, respectively, and the endothermicity of (f) is 42.54(38.11) kcal mol{sup −1}. Quasiclassical trajectory computations of cross sections, scattering (θ) and initial attack (α) angle distributions, as well as translational and internal energy distributions are performed for the F{sup −} + CH{sub 3}F(v = 0) reaction using the new PES. Apart from low collision energies (E{sub coll}), the S{sub N}2 excitation function is nearly constant, the abstraction cross sections rapidly increase with E{sub coll} from a threshold of ∼40 kcal mol{sup −1}, and retention trajectories via double inversion are found above E{sub coll} = ∼ 30 kcal mol{sup −1}, and at E{sub coll} = ∼ 50 kcal mol{sup −1}, the front-side attack cross sections start to increase very rapidly. At low E{sub coll}, the indirect mechanism dominates (mainly isotropic backward-forward symmetric θ distribution and translationally cold products) and significant long-range orientation effects (isotropic α distribution) and barrier recrossings are found. At higher E{sub coll}, the S{sub N}2 reaction mainly proceeds with direct rebound mechanism (backward scattering and hot product translation)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Quantum Computing for Energy-Related Applications

Growing interest in quantum computing and simulations have created opportunities for its deployment to improve processes pertaining to energy production, distribution, and consumption. While quantum computing is considered as a paradigm shift in our basic understanding of physical computation, effective implementation of quantum computing in energy applications also depends on progress and development in the dimensions of both quantum computing hardware and quantum computing algorithms. To fully address the status and future challenges of quantum information science (QIS) applied within the energy sector, in this presentation, we firstly summarize recent advancements on the applications of quantum computing to energy infrastructure and materials, complex energy system processes, advanced manufacturing, and energy system security. Then, we will demonstrate the results of quantum computing both on a simulator and a quantum device accessing from OLCF. Our first example is to use the variational quantum eigensolver (VQE) with a unitary coupled cluster with singles and doubles (UCCSD) ansatz to simulate a series of LixHyq molecules (q=-1, 0, +1). The obtained results showed that the quantum computing VQE-UCCSD is comparable to classical CCSD for small systems like LiH with respect to full configuration interaction (FCI). Targeting on CO2 capture application, our second example is to use VQE to quantify molecular vibrational energies and reaction pathways between CO2 and a simplified amine-based solvent model—NH3 to form H2NCOOH. This research showcases quantum computing applications in the study of CO2 capture reactions.

Duan, Yuhua↗
DOE OSTI2024

Strategies to Obtain Reliable Energy Landscapes from Embedded Multireference Correlated Wavefunction Methods for Surface Reactions

Embedded correlated wavefunction (ECW) theory is a powerful tool for studying ground- and excited-state reaction mechanisms and associated energetics in heterogeneous catalysis. Several factors are important to obtaining reliable ECW energies, critically the construction of consistent active spaces (ASs) along reaction pathways when using a multireference correlated wavefunction (CW) method that relies on a subset of orbital spaces in the configuration interaction expansion to account for static electron correlation, e.g., complete AS self-consistent field theory, in addition to the adequate partitioning of the system into a cluster and environment, as well as the choice of a suitable basis set and number of states included in excited-state simulations. Here, in this work, we conducted a series of systematic studies to develop best-practice guidelines for ground- and excited-state ECW theory simulations, utilizing the decomposition of NH 3 on Pd(111) as an example. We determine that ECW theory results are relatively insensitive to cluster size, the aug-cc-pVDZ basis set provides an adequate compromise between computational complexity and accuracy, and that a fixed-clean-surface approximation holds well for the derivation of the embedding potential. Additionally, we demonstrate that a merging approach, which involves generating ASs from the molecular fragments at each configuration, is preferable to a creeping approach, which utilizes ASs from adjacent structures as an initial guess, for the generation of consistent potential energy curves involving open-d-shell metal surfaces, and, finally, we show that it is essential to include bands of excited states in their entirety when simulating excited-state reaction pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

An overview of selected current approaches to the characterization of aqueous inorganic clusters

This Perspective article highlights some of the traditional and non-traditional analytical tools that are currently used to characterize aqueous inorganic nanoscale clusters and polyoxometalate ions. The techniques discussed in this article include nuclear magnetic resonance spectroscopy (NMR), small angle X-ray scattering (SAXS), dynamic and phase analysis light scattering (DLS and PALS), Raman spectroscopy, and quantum mechanical computations (QMC). For each method we briefly describe how it functions and illustrate how these techniques are used to study cluster species in the solid state and in solution through several representative case studies. In addition to highlighting the utility of these techniques, we also discuss limitations of each approach and measures that can be applied to circumvent such limits as it pertains to aqueous inorganic cluster characterization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Scale-up Unlearnable Examples Learning with High-performance Computing

Recent advancements in AI models, like ChatGPT, are structured to retain user interactions, which could inadvertently include sensitive healthcare data. In the healthcare field, particularly when radiologists use AI-driven diagnostic tools hosted on online platforms, there is a risk that medical imaging data may be repurposed for future AI training without explicit consent, spotlighting critical privacy and intellectual property concerns around healthcare data usage. Addressing these privacy challenges, a novel approach known as Unlearnable Examples (UEs) has been introduced, aiming to make data unlearnable to deep learning models. A prominent method within this area, called Unlearnable Clustering (UC), has shown improved UE performance with larger batch sizes but was previously limited by computational resources (e.g., a single workstation). To push the boundaries of UE performance with theoretically unlimited resources, we scaled up UC learning across various datasets using Distributed Data Parallel (DDP) training on the Summit supercomputer. Our goal was to examine UE efficacy at high-performance computing (HPC) levels to prevent unauthorized learning and enhance data security, particularly exploring the impact of batch size on UE’s unlearnability. Utilizing the robust computational capabilities of the Summit, extensive experiments were conducted on diverse datasets such as Pets, MedMNist, Flowers, and Flowers102. Our findings reveal that both overly large and overly small batch sizes can lead to performance instability and affect accuracy. However, the relationship between batch size and unlearnability varied across datasets, highlighting the necessity for tailored batch size strategies to achieve optimal data protection. The use of Summit’s high-performance GPUs, along with the efficiency of the DDP framework, facilitated rapid updates of model parameters and consistent training across nodes. Our results underscore the critical role of selecting appropriate batch sizes based on the specific characteristics of each dataset to prevent learning and ensure data security in deep learning applications. The source code is publicly available at https: // github. com/ hrlblab/ UE_ HPC .

Zhu, Yanfan [Vanderbilt University, Nashville, TN,↗
DOE OSTI2018

Exact diagonalization library for quantum electron models

We present an exact diagonalization C++ template library (EDLib) for solving quantum electron models,including the single-band finite Hubbard cluster and the multi-orbital impurity Anderson model. Theobservables that can be computed using EDLib are single particle Green’s functions and spin–spincorrelation functions. This code provides three different types of Hamiltonian matrix storage that canbe chosen based on the model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Evaluating lightweight unsupervised online IDS for masquerade attacks in CAN

Vehicular controller area networks (CANs) are susceptible to masquerade attacks by malicious adversaries. In masquerade attacks, adversaries silence a targeted ID and then send malicious frames with forged content at the expected timing of benign frames. As masquerade attacks could seriously harm vehicle functionality and are the stealthiest attacks to detect in CAN, recent work has devoted attention to compare frameworks for detecting masquerade attacks in CAN. However, most existing works report offline evaluations using CAN logs already collected using simulations that do not comply with the domain’s real-time constraints. Here we contribute to advance the state of the art by presenting a comparative evaluation of four different non-deep learning (DL)-based unsupervised online intrusion detection systems (IDS) for masquerade attacks in CAN. Our approach differs from existing comparative evaluations in that we analyze the effect of controlling streaming data conditions in a sliding window setting. In doing so, we use realistic masquerade attacks being replayed from the ROAD dataset. We show that although evaluated IDS are not effective at detecting every attack type, the method that relies on detecting changes in the hierarchical structure of clusters of time series produces the best results at the expense of higher computational overhead. We discuss limitations, open challenges, and how the evaluated methods can be used for practical unsupervised online CAN IDS for masquerade attacks.

Anomaly detection↗
DOE OSTI2024

“Best” Iterative Coupled-Cluster Triples Model? More Evidence for 3CC

To follow up on the unexpectedly good performance of several coupled-cluster models with approximate inclusion of 3-body clusters we performed a more complete assessment of the 3CC method for accurate computational thermochemistry in the standard HEAT framework. New spin-integrated implementation of the 3CC method applicable to closed- and open-shell systems utilizes a new automated toolchain for derivation, optimization, and evaluation of operator algebra in many-body electronic structure. We found that with a double-ζ basis set the 3CC correlation energies and their atomization energy contributions are almost always more accurate (with respect to the CCSDTQ reference) than the CCSDT model as well as the standard CCSD(T) model. The mean absolute errors in cc-pVDZ {3CC, CCSDT, and CCSD(T)} electronic (per valence electron) and atomization energies relative to the CCSDTQ reference for the HEAT data set, were {24, 70, 122} μE h /e and {0.46, 2.00, 2.58} kJ/mol, respectively. The mean absolute errors in the complete-basis-set limit {3CC, CCSDT, and CCSD(T)} atomization energies relative to the HEAT model reference, were {0.52, 2.00, and 1.07} kJ/mol, The significant and systematic reduction of the error by the 3CC method and its lower cost than CCSDT suggests it as a viable candidate for post- CCSD(T) thermochemistry applications, as well as the preferred alternative to CCSDT in general.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗